The Fermi GBM Gamma-Ray Burst Spectral Catalog: Four Years Of Data

In this catalog we present the updated set of spectral analyses of GRBs detected by the Fermi Gamma-Ray Burst Monitor (GBM) during its first four years of operation. It contains two types of spectra, time-integrated spectral fits and spectral fits at the brightest time bin, from 943 triggered GRBs. Four different spectral models were fitted to the data, resulting in a compendium of more than 7500 spectra. The analysis was performed similarly, but not identically to Goldstein et al. 2012. All 487 GRBs from the first two years have been re-fitted using the same methodology as that of the 456 GRBs in years three and four. We describe, in detail, our procedure and criteria for the analysis, and present the results in the form of parameter distributions both for the observer-frame and rest-frame quantities. The data files containing the complete results are available from the High-Energy Astrophysics Science Archive Research Center (HEASARC).Comment: Accepted for publication in ApJ

The 3rd Fermi GBM Gamma-Ray Burst Catalog: The First Six Years

Since its launch in 2008, the Fermi Gamma-ray Burst Monitor (GBM) has triggered and located on average approximately two gamma-ray bursts (GRB) every three days. Here we present the third of a series of catalogs of GRBs detected by GBM, extending the second catalog by two more years, through the middle of July 2014. The resulting list includes 1405 triggers identified as GRBs. The intention of the GBM GRB catalog is to provide information to the community on the most important observables of the GBM detected GRBs. For each GRB the location and main characteristics of the prompt emission, the duration, peak flux and fluence are derived. The latter two quantities are calculated for the 50-300~keV energy band, where the maximum energy release of GRBs in the instrument reference system is observed, and also for a broader energy band from 10-1000 keV, exploiting the full energy range of GBM's low-energy NaI(Tl) detectors. Using statistical methods to assess clustering, we find that the hardness and duration of GRBs are better fitted by a two-component model with short-hard and long-soft bursts, than by a model with three components. Furthermore, information is provided on the settings and modifications of the triggering criteria and exceptional operational conditions during years five and six in the mission. This third catalog is an official product of the Fermi GBM science team, and the data files containing the complete results are available from the High-Energy Astrophysics Science Archive Research Center (HEASARC).Comment: 225 pages, 13 figures and 8 tables. Accepted for publication in Astrophysical Journal Supplement 201

PDBe: improved accessibility of macromolecular structure data from PDB and EMDB

© 2015 The Authors. Published by OUP. This is an open access article available under a Creative Commons licence. The published version can be accessed at the following link on the publisher’s website: https://doi.org/10.1093/nar/gkv1047The Protein Data Bank in Europe (http://pdbe.org) accepts and annotates depositions of macromolecular structure data in the PDB and EMDB archives and enriches, integrates and disseminates structural information in a variety of ways. The PDBe website has been redesigned based on an analysis of user requirements, and now offers intuitive access to improved and value-added macromolecular structure information. Unique value-added information includes lists of reviews and research articles that cite or mention PDB entries as well as access to figures and legends from full-text open-access publications that describe PDB entries. A powerful new query system not only shows all the PDB entries that match a given query, but also shows the 'best structures' for a given macromolecule, ligand complex or sequence family using data-quality information from the wwPDB validation reports. A PDBe RESTful API has been developed to provide unified access to macromolecular structure data available in the PDB and EMDB archives as well as value-added annotations, e.g. regarding structure quality and up-to-date cross-reference information from the SIFTS resource. Taken together, these new developments facilitate unified access to macromolecular structure data in an intuitive way for non-expert users and support expert users in analysing macromolecular structure data.The Wellcome Trust [88944, 104948]; UK Biotechnology and Biological Sciences Research Council [BB/J007471/1, BB/K016970/1, BB/M013146/1, BB/M011674/1]; National Institutes of Health [GM079429]; UK Medical Research Council [MR/L007835/1]; European Union [284209]; CCP4; European Molecular Biology Laboratory (EMBL). Funding for open access charge: The Wellcome Trust.Published versio

The Novel Deacetylase Inhibitor AR-42 Demonstrates Pre-Clinical Activity in B-Cell Malignancies In Vitro and In Vivo

While deacetylase (DAC) inhibitors show promise for the treatment of B-cell malignancies, those introduced to date are weak inhibitors of class I and II DACs or potent inhibitors of class I DAC only, and have shown suboptimal activity or unacceptable toxicities. We therefore investigated the novel DAC inhibitor AR-42 to determine its efficacy in B-cell malignancies.In mantle cell lymphoma (JeKo-1), Burkitt's lymphoma (Raji), and acute lymphoblastic leukemia (697) cell lines, the 48-hr IC(50) (50% growth inhibitory concentration) of AR-42 is 0.61 microM or less. In chronic lymphocytic leukemia (CLL) patient cells, the 48-hr LC(50) (concentration lethal to 50%) of AR-42 is 0.76 microM. AR-42 produces dose- and time-dependent acetylation both of histones and tubulin, and induces caspase-dependent apoptosis that is not reduced in the presence of stromal cells. AR-42 also sensitizes CLL cells to TNF-Related Apoptosis Inducing Ligand (TRAIL), potentially through reduction of c-FLIP. AR-42 significantly reduced leukocyte counts and/or prolonged survival in three separate mouse models of B-cell malignancy without evidence of toxicity.Together, these data demonstrate that AR-42 has in vitro and in vivo efficacy at tolerable doses. These results strongly support upcoming phase I testing of AR-42 in B-cell malignancies

In Support of a Patient-Driven Initiative and Petition to Lower the High Price of Cancer Drugs

Comment in Lowering the High Cost of Cancer Drugs--III. [Mayo Clin Proc. 2016] Lowering the High Cost of Cancer Drugs--I. [Mayo Clin Proc. 2016] Lowering the High Cost of Cancer Drugs--IV. [Mayo Clin Proc. 2016] In Reply--Lowering the High Cost of Cancer Drugs. [Mayo Clin Proc. 2016] US oncologists call for government regulation to curb drug price rises. [BMJ. 2015

Some Aspects of Latent Structure Analysis

Latent structure models involve real, potentially observable variables and latent, unobservable variables. The framework includes various particular types of model, such as factor analysis, latent class analysis, latent trait analysis, latent profile models, mixtures of factor analysers, state-space models and others. The simplest scenario, of a single discrete latent variable, includes finite mixture models, hidden Markov chain models and hidden Markov random field models. The paper gives a brief tutorial of the application of maximum likelihood and Bayesian approaches to the estimation of parameters within these models, emphasising especially the fact that computational complexity varies greatly among the different scenarios. In the case of a single discrete latent variable, the issue of assessing its cardinality is discussed. Techniques such as the EM algorithm, Markov chain Monte Carlo methods and variational approximations are mentioned